1 Best APIs for Quantity Parsing in Nigeria

Zestful is a recipe ingredient parsing API that converts natural language ingredient strings — the kind found in recipe texts — into structured, machine-readable data. When a recipe says "2 cups of sifted all-purpose flour" or "1 medium onion, finely chopped," Zestful parses that string and returns a structured object containing the ingredient name, quantity, unit of measurement, and preparation instructions as separate, discrete fields. This structured parsing is the foundation for a wide range of food technology applications. Nutrition calculation requires knowing the specific ingredient and its quantity in a standardized unit. Shopping list generation needs ingredient names separated from quantities. Ingredient search and filtering requires clean ingredient names without surrounding text. Recipe scaling requires parseable quantities that can be multiplied. Without automated ingredient parsing, all of these features either require manual data entry or produce unreliable results from naïve string matching. The parsing model was trained on a large corpus of English-language recipe data and handles the wide variety of ways recipe authors express ingredients — fractional quantities, range quantities, alternative quantities, parenthetical notes, and culturally-specific ingredient names. It returns a confidence score with each parse, allowing applications to handle low-confidence parses with appropriate fallback behavior (such as keeping the raw string and flagging it for manual review). Bulk parsing mode accepts multiple ingredient strings in a single API call, making it efficient for processing entire recipes or large ingredient databases in one request. This is important for Nigerian food tech platforms that are migrating or importing legacy recipe databases that were stored as unstructured text. For Nigerian food technology applications, Zestful addresses a real data challenge. Nigerian cuisine involves a rich variety of ingredients — stockfish, iru (locust beans), uziza leaves, crayfish, ogiri, ede (cocoyam), egusi, ogbono, and hundreds of regional-specific items — that appear in recipe texts with varied names, spellings, and preparation descriptions. While Zestful's training data is primarily English-language and may have less coverage of Nigerian-specific ingredient names compared to Western ingredients, it still provides significant value for the structural parsing task, and Nigerian developers can supplement it with a custom ingredient name lookup for local ingredients. Nigerian recipe applications that aggregate recipes from multiple sources (food blogs, cookbooks, user submissions) face the challenge of inconsistent ingredient formatting across sources. Zestful normalizes this into a consistent structure, enabling cross-recipe comparison, ingredient search, and nutritional analysis across the aggregated recipe database. Nigerian nutrition and health tracking applications that help users log meals can use Zestful to parse ingredient strings when users enter recipe-based meals — extracting quantities and ingredient names to look up nutritional values in a food composition database, rather than requiring users to enter each ingredient component manually. The API pricing is usage-based at $0.002 per ingredient parse, making it cost-effective for moderate-volume use without a subscription commitment. Authentication uses a Bearer token API key. REST calls accept the ingredient string as a JSON parameter and return the parsed components as a structured JSON response. Zestful's confidence scores for each parse component allow Nigerian applications to implement tiered handling — automatically accepting high-confidence parses, flagging medium-confidence parses for review, and rejecting very-low-confidence parses entirely. This graduated handling prevents bad parses from silently corrupting nutritional data or shopping list entries.